When a market participant in the public securities market (or any financial market) needs to execute a large (block) order, that participant faces a significant challenge: achieving an economically efficient transaction in a timely manner. As used herein, the term “market participant” refers to any person or firm with the ability to trade securities; examples of market participants include broker-dealers, institutions, hedge funds, statistical arbitrage and other proprietary trading operations, and private investors trading on electronic communication networks (ECNs). There are a number of reasons why the timely and efficient execution of large orders is a particular challenge. First and foremost, the move to decimalization, coupled with a drastic increase in the number of trading venues, has driven down the average trade size from 1,187 shares in December of 2000 to 393 shares in December of 2004 (NYSE Fact Book online). As a result, the display of a large block is an anomaly, and tends to create adverse price action. This adverse action is driven by many factors, including “front running” (buying or selling activity by other market participants in anticipation of price movement resulting from the large revealed order), and the general increase in trading activity, based solely on the assumption that a large buy (or sell) interest indicates that a stock is worth more (or less) than its current price.
In order to avoid, or at least reduce, the negative market impact caused by the display of large orders, most participants choose to divide larger orders into a series of smaller orders, which they then enter through multiple trading venues over an extended period of time. This tactic can reduce adverse market impact and protect the confidentiality of a larger order. However, with this approach a market participant has no guarantee of enough fills to complete the larger order, or any idea of the range of prices she will need to accept in order to complete the transaction. As a result, confidentiality is maintained, but in exchange the market participant sacrifices the efficiency of a quick fill at a single, known price.
Market participants often turn to capital providers (also called dealers and market makers) when they do not want to accept the confidentiality vs. efficiency trade-off offered by exchanges, alternate trading systems, and ECNs. However, a market participant who chooses to work with a capital provider still faces a similar set of trade-offs: information leakage vs. quality of spread. Because a capital provider commits its own capital, when a market participant makes a Request for Quote (RFQ), a capital provider must respond with a quote that reflects the risk inherent in the position it will own if the transaction executes. The degree of risk is driven by a number of factors, including the type of stock, the price of the stock, the stock's liquidity, general market conditions, and the behavior of the market participant post-execution. Because the capital provider must consider so many risk factors in pricing its response, the more information a capital provider has about a request, the more accurate its risk-assessment and the tighter the responding spread.
Therefore, to enable a capital provider to offer the most competitive spread possible, a market participant must reveal a great deal of very valuable information: who she is, what stock she wants to trade, the size of her order, the side of her order, and the price that will satisfy her. While this information enables capital providers to offer the tightest spreads, it also represents a real option that the capital provider can use to his own advantage. It is difficult to distinguish, on the one hand, information that is legitimately required to estimate risk, and on the other hand, information that could be exploited by the capital provider's proprietary trading desk outside the scope of the customer's interests. For example, an institutional order seeking capital might be the first slice of a multi-million share order, and the overall strategy and price aggression for completing the full order must remain confidential to ensure that this strategy and the entire block can be properly executed.
Thus, a fundamental problem for capital providers and their customers lies in the fact that much of the information that is required to evaluate accurately the risk of providing capital is by its nature too confidential for a market participant to share with the capital provider. If a market participant chooses to limit the information she gives to the capital provider in the interest of protecting the option value of her trade information, she does reduce the likelihood that her order information will be used against her. But at the same time, providing less information reduces the accuracy of the capital provider's risk assessment, thereby increasing the size of the spread.
Up to this point, market participant/capital provider transactions have been plagued by the inefficiencies inherent in a system that forces both parties to make significant tradeoffs: market participants must choose between tighter spreads and potential information leakage, and capital providers must choose between customer satisfaction and potential risk. At present, the inventors are aware of three pending applications that attempt to address these inefficiencies, though they do so in ways that are markedly different from the subject system. It should be noted that the discussion herein of these applications does not imply that they are prior art, since this application claims priority to applications filed as early as June 2000.
United States Patent Application Publication No. 20050246261, “Method and System for Block Trading of Securities,” to Stevens et al. and assigned to Bank of America, teaches an “automated dealer system that formulates customized, risk-controlled, two-sided indicative quotations for block quantities of a security.” This system attempts to address the information/spread quality conflict by offering a spectrum of quote customizations. At the end of the spectrum focused on confidentiality, a generic quote is adjusted according to “the size of the block, and at least one historical characteristic of the security. Historical characteristics for securities can include a historical spread, volatility, liquidity, or other characteristics.” At the other end of the spectrum, focused on quality of the spread, the quote is further customized through the application of a “client-specific profitability constant,” that associates the market-participant's identity and trading history to his RFQ. While this system improves on the traditional dealer market by enabling market participants to match their quote customization level to the point on the confidentiality/spread quality spectrum that best suits their needs, the system still forces a tradeoff between quote quality and confidentiality.
United States Patent Application Publication No. 20030033239, “Request for Quote (RFQ) and Inside Markets,” to Gilbert et al., also attempts to address the challenges associated with anonymous capital providing. This application teaches “systems and methods for rule-based bilateral negotiation of quotes in response to request for quotes (RFQ) and inside markets.” The system enables market participants and capital providers (CPs) to share a range of user-selected data points in a controlled dialogue or rules-based negotiation. Since all information in the negotiation is shared directly with the CPs, it does not provide a means to obtain a better spread while protecting the confidentiality of the information used to estimate risk. It also does not enable reducing the option value of the information.
The primary focus of the Gilbert system is to ensure that information shared between market participants and capital provider(s) is protected, rather than trying to minimize the amount of information that needs to be shared. Another significant aspect of this system is that it enables rules-based negotiation “that emulates a voice request for a final price.” But, as with the Bank of America system, the quality of the quote generated through this system is ultimately tied to the amount of information shared between the two parties. Although the move towards “policing” behavior is a dramatic improvement on traditional dealer markets, the fact that there are “rules” does not change the reality that this system requires participants to share confidential information in order to achieve the best quote. For example, if a market participant uses this system, and chooses to remain anonymous but indicates that she trades for a hedge fund, she is likely to receive a bigger spread, even if her historic trading behavior does not warrant a larger spread. To achieve the best spread in Gilbert's system, the “well behaved” hedge fund trader would ultimately have to reveal her identity or past trading history to get a fair quote.
The system of United States Patent Application Publication No. 20020091617, “Trading program for interacting with market programs on a platform,” to Christopher Keith, is a complex trading platform that attempts to address the inefficiencies found in all “conventional financial instrument trading systems.” The essential goal of Keith's system is to enable market participants and capital providers to input their order and liquidity providing requirements via intelligent agents which “decide” how, when, and where to input and execute orders based on criteria pre-programmed by the users. The purpose of this system is to provide users with a flexible platform that offers the speed and convenience associated with electronic trading, without losing the advantages of floor trading and without forcing traders to abandon the use of “private, interpersonal agreements and arrangements that have been considered unsuitable for automation in conventional trading systems.”
In order to achieve this goal, Keith's system permits market participants to employ “electronic liquidity finder” (ELF) programs, and market providers to employ “umpires” to act on their behalf inside a black box. ELFs are described as “virtual floor brokers working at electronic speeds,” and umpires are “formal or informal markets that define and implement the rules of engagement by which information is exchanged between ELFs.” ELFs and umpires interact through a wide range of complex and nuanced rules that allow traders to combine the benefits of an electronic trading platform with a level of customization and personalization associated with floor-based trading.
While Keith's system does offer traders more control over the information leakage related to their orders, it is not a Request For Quote system: CPs are able to submit trading algorithms, but they are not able to decide on a case by case basis (according to order information or a risk classification system) whether or not they should respond to an RFQ. Likewise, the market participants are not able to review a plurality of quotes and decide, looking at their own strategic interests, whether or not to execute a CP's quote.